Experiments

Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).

• VIRGO: computational prediction of gene functions.

  PMID 16845022 · PMC1538839 · Nucleic acids research · 2006 · 8 claims · 6 setups

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  VIRGO constructs a functional linkage network (FLN) from gene expression and molecular interaction data, labels genes with GO annotations, and propagates these labels to predict functions of unlabelled genes

  cerevisiae sapiens leave-one-out gene protein-protein

• Identification of candidate disease genes by integrating Gene Ontologies and protein-interaction networks: case study of primary immunodeficiencies.

  PMID 19073697 · PMC2632920 · Nucleic acids research · 2009 · 8 claims · 5 setups

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  Combining high protein-interaction network scores with significant PID-related GO terms identifies novel PID candidate genes

  immunome known protein-interaction gene comparative

• Analysis of protein sequence and interaction data for candidate disease gene prediction.

  PMID 17020920 · PMC1636487 · Nucleic acids research · 2006 · 8 claims · 7 setups

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  Combining CPS and CMP using known disease genes as input achieves sensitivity 0.52 and specificity 0.97, reducing candidate lists 13-fold

  ophid biocarta kegg pfam-annotated common benchmarking multiple-interval

• Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes.

  PMID 18053250 · PMC2246260 · Genome biology · 2007 · 8 claims · 4 setups

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  Loss-of-function phenotypes in yeast are predictable from a gene's connections in a functional gene network via guilt-by-association.

  saccharomyces guilt-by-association comparison network-guided

• PlasmoDraft: a database of Plasmodium falciparum gene function predictions based on postgenomic data.

  PMID 18925948 · PMC2605471 · BMC bioinformatics · 2008 · 8 claims · 4 setups

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  Gonna, a supervised k-nearest-neighbor Guilt-By-Association predictor, proposes GO annotations for a gene based on similarity of its transcriptome, proteome, or interactome profile to genes already annotated by GeneDB

  plasmodium genedb-annotated k-nn leave-one-out